ABSTRACT
One of the major questions for economic game theory in recent years has been “How do humans learn to behave in strategic situations?” Since the demise of the educative refinement program of game theory, hope has arisen that dynamic learning models might be able to resolve the predictive impotency of equilibrium theories. We will review these learning models and present “horse race” evidence that favors Rule Learning. We will also show that the framework of Rule Learning can easily accommodate behavioral rules like aspiration-based experimentation, reciprocity-based cooperation, warm glow and tit-for-tat. Finally, we will address weaknesses of the Rule Learning model, as well as how the model could be applied to extensive-form games.
